This study aims to examine the asymmetric nexus between CO₂ emissions and renewable energy and economic and population growth in seven East African countries (EACs) at the regional level and country levels. Common correlated effect means group (CCEMG), nonlinear autoregressive distributed lagged (NARDL), and causality tests were employed for the panel data from 1980 to 2016. The main findings are as follows: (1) Renewable energy consumption negatively affects CO₂ emissions, while economic and population growth positively affect CO₂ emissions at the regional level. (2) The findings of asymmetric and symmetric linkages between CO₂ emissions and its determinants (economic and population growth and renewable energy) are very volatile across the country levels. (3) The causality hypotheses are different across the country and regional levels. (4) This study shows the renewable energy growth nexus, wherein renewable energy positively affects economic growth at the regional level. Lastly, the study suggests potential policy implications for effectively reducing CO₂ emissions as well as growing the economy at the regional level.

This study focused on the existence and uniqueness(EU) and stability of the solution for a system of fractional differential equations(FDEs) via Atangana-Baleanu derivative in the sense of Caputo (ABC) with \(\phi_{p}\)-Laplacian operator. Green function \( \mathcal{G}^{\eth}(t,s)\), \(m<\eth<m+1\), \(m\geq4\) used for converting the suggested problem to an integral equation. Guo-Krasnoselskii theorem used for proving the EU of solution for the suggested problem. The stability of the solution was derived by Hyers-Ulam stability method(HUS). One illustrative example is used for manifesting the results.

Oil production task allocation (OPTA) is affected by various factors, and each one has a different impact on oil production. Therefore, the fair distribution of production task to each production branch is really a hard work for an oil company, so a fair allocation based on contribution rate (ABCR) has been proposed to solve this problem in this paper. The algorithm of ABCR, unlike other existing algorithms, takes into account the differences of members’ contribution (DMC), which can be expressed by member contribution rate (MCR) based on the certainty and uncertainty factors. Two steps are implemented to gain the differences of members’ contribution. First, we use Principal Component Analysis (PCA) to reduce factors for certain factor and construct a new factor with Analytic Hierarchy Process (AHP) for uncertain factor. Then, the MCR is evaluated by AHP. Based on member contribution rate, member goal, and alliance target, a fair allocation can be obtained by ABCR. Finally, we propose an evaluation criterion for allocation. Case study shows that the resource allocation results of ABCR not only are more reasonable than those of the other methods but also can prevent unfair allocation and enhance the production environment, thereby improving the enthusiasm for production.

Background: Infectious diseases are predominantly within poor population living in low-income countries, while are either treatable or preventable with existing medicines in the first occurring. The highlighted cause is some government choose to spend national budget on several projects do not coincide the basic needs and demands of the population. The objectives of this study were to 1) compare the performance between new cases and deaths caused by diseases; 2) show the effect of gross national income (GNI) in the mortalities reduction, and 3) assess potential evolution in eradicating mortalities in East African countries. Method: WHO database contains data on several responses (new cases of Malaria, Neonates protected at birth against neonatal tetanus, mortalities from tuberculosis among HIV-negative people and new cases of leprosy) recorded from 2004 to 2015. IMB SPSS modeler and Origin 8 were used especially, One-way ANOVA and Pearson’s correlation to achieve the objectives of the study. Results: The p-values for either Levene’ and Brown-Forsythe compared with 0.05 significant level for testing the performance between countries, correlation between GNI with leprosy is -0.5 to -1.0, in five countries, with TB is closer t0 -1.0 in four countries, with deaths from Malaria, is -0.5 to -1.0 in three countries, and new cases from Malaria and protected neonates is 0.5 to 1.0. Conclusion: The relationship between GNI and new cases and deaths indicate the weak effect of GNI in the process of eradicating mortalities, therefore, the government should prioritize the healthcare and use a national budget to monitoring the all complications related to infectious diseases. Key wards: infectious diseases, eradicating mortalities, gross national income